<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>Continual Learning on Tolga Dimlioglu</title><link>https://tolgadimli.github.io/tags/continual-learning/</link><description>Recent content in Continual Learning on Tolga Dimlioglu</description><generator>Hugo -- 0.147.2</generator><language>en</language><lastBuildDate>Sun, 28 May 2023 00:00:00 +0000</lastBuildDate><atom:link href="https://tolgadimli.github.io/tags/continual-learning/index.xml" rel="self" type="application/rss+xml"/><item><title>Continual Facial Expression Recognition: A benchmark</title><link>https://tolgadimli.github.io/papers/paper6/</link><pubDate>Sun, 28 May 2023 00:00:00 +0000</pubDate><guid>https://tolgadimli.github.io/papers/paper6/</guid><description>We introduce ConFER, a continual-learning benchmark for facial expression recognition that evaluates how well popular CL methods adapt to real-world, incremental data without catastrophic forgetting, demonstrating state-of-the-art performance across multiple FER datasets and highlighting the benefits of CL for robust affective computing.</description></item></channel></rss>